Statistical research is a critical part of dissertation writing task that is taken up at the master’s level. It is at this stage that students get familiar with a number of statistical tools and methodologies. They have to learn these tools and determine which test will be the most appropriate for the study that they are going to undertake. Grasping so many things and then coming to the right decision is not easy and needs some mentoring.
360 Dissertations offers focused dissertation statistics help service to ensure that students are able to learn about the various tools without hassles. There is a systematic approach followed to teach students about statistical methods. If you are a PhD or Master’s candidate looking for help with chapter 4 of your dissertation which is data analysis, you have reached the right place. Our dissertation statistics help service provides help with descriptive tests, inferential tests, hypothesis testing, predictive analysis and interpretation report. Our statisticians are well versed with SPSS, AMOS, STATA, E-Views, R and Minitab.
We help you with data collection by suggesting the most suitable sample size and sample group. You can also get dissertation data analysis help and assistance for preparation of questionnaire, so that it elucidates the targeted information.
Amongst the various statistical tools and programs, like SPSS, SAS, Stata, Amos, R, E-views, we help you to choose the one which will lead you to the desired result and will match the requirements of the project. If there is a certain tool prescribed by the college, students must inform about the same and our tutors will help to apply them.
Through accurate application of tools and tests, we create modules that explain each step of the analysis. There are several sample modules for students to understand the method of creation and presentation. You can ask for sample modules from our team.
This service also looks after the graphical representation of the dissertation. We prepare graphs and tables which are appropriate as per the modules. These complement the text and computational analysis.
The results are interpreted in an appropriate manner and explained for the chapter of results and discussion. There are many issues that are faced in this chapter and reliable guidance by our statisticians ensures that the results are understood by reviewers.